Help in averaging climate data

I am a novice in matlab and looking for help with calculating average monthly data from hourly data.
I have the data for full year in one file and have multiple txt files for different years. Column 1 is year, column 2 is month of year (1 to 12), column 3 is day of month and column 4 is hour of day (0 to 23). Looking forward to some guidance on how to do this.
Thanks in advance

5 Comments

Have you imported the data into MATLAB? I.e. do you have the data stored in a N-by-4 dimensional matrix yet?
So, does a row of the data looks like
[1990, 2, 28, 23] % for 11pm Feb 28 1990
Where is the climate data? Is that stored in another column? or a separate vector?
This is how I imported the data to matlab:
D = importdata('metdata1.txt')
D =
data: [8760x13 double]
textdata: {8760x1 cell}
rowheaders: {8760x1 cell}
So, which columns of the 13 are the four you describe above, and which one is the climate data?
And this is what the first row looks like if I am doing it right:
D.data(1,:)
ans =
1.0e+03 *
Columns 1 through 12
1.9730 0.0010 0.0010 0 -0.9990 -0.0999 -0.0090 -0.9999 -0.9999 -0.9999 -0.9999 -0.0990
Column 13
-0.0990

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Answers (2)

Sam
Sam on 6 Jun 2013
Yes, I have imported them into matlab
I'll suppose you have the climate data in column five of an array, A, with the year, month, day, and hour in its columns 1, 2, 3, and 4, respectively.
[u,~,ix] = unique(A(:,1:2),'rows');
B = [u,accumarray(ix,A(:,5))./accumarray(ix,1)];

5 Comments

Sam
Sam on 6 Jun 2013
Edited: Sam on 6 Jun 2013
Hi Roger, Thanks, this seems to produce a matrix for the 12 months. But how not to take into account the "999.9" data i.e. the missing value data in the column?
It should produce a row for every year-month combination, not just for 12 months.
If you can fully(!) describe the "missing value" situation, perhaps a solution could be found. As things stand, I can only guess at what you mean.
Actually data for different years are in different files in the data column, a data value of "999.9" means a missing value so not to be considered in the a calculation. Now it is averaging over the entire column for unique values of month.
You could initially remove all rows with the "999.9" data values:
A = A(A(:,5)~=999.9,:);
However, it might be better to allow some tolerance for rounding differences:
A = A(abs(A(:,5)-999.9)<100*eps(999.9),:);
Thank you guys.

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Sam
on 6 Jun 2013

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on 14 Jul 2015

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